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This study presents a new method for selecting monitoring wells for optimal evaluation of groundwater quality. The basic approach of this work is motivated by difficulties in interpolating groundwater quality from information collected for only few sampled wells. The well selection relies on other existing data relevant to contaminant distribution in the sampling domain, e.g. predictions of models which rely on past measurements. The objective of this study is to develop a method of selecting the optimal wells, from which measurements could best serve some external model, e.g. a kriging system for characterizing the entire plume distribution, a flow-and-transport model for predicting a future distribution, or an inverse model for locating contaminant sources or estimating aquifer parameters. The decision variable at each sampling round determines the specific wells to be sampled. The study objective is accomplished through a spatially-continuous utility density function (UDF) which describes the utility of sampling at every point. The entire methodology which utilizes the UDF in conjunction with a sampling algorithm is entitled the UDF method. By applying calculations in steady and unsteady state sampling domains the effectiveness of the UDF method is demonstrated. [ABSTRACT FROM AUTHOR]